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PurposeConstruction contractors in Palestine, as in many other developing countries, suffer from many problems. One of their main problems is their inability to meet contractual requirements, such as completing projects within time, at the agreed cost and to the desired quality. Therefore, this paper aims to investigate the causes of the non-fulfillment of contractual requirements in three different types of projects: building, road and electro-mechanical projects.Design/methodology/approachTwo methods were adopted to collect the data – qualitative and quantitative. In total, 65 causes were identified from the literature and qualitative semi-structured interviews with professional experts. These causes were classified into five categories: managerial, financial, contractor capabilities, regulations and laws and political. In the quantitative approach, a questionnaire was developed and then distributed to 50 professional experts: 20 building experts, 15 road experts and 15 experts in electro-mechanical projects. A five-point Likert scale was used to assess the importance, from the perspective of the subject matter experts, of the causes that had been identified. About 35 responses, which represent a combined response rate of 70%, were received. The quantitative data were analyzed using descriptive statistics, with the mean, standard deviation and degree of importance for each of the identified causes being determined, and the SPSS software platform used to rank them.FindingsThe results reveal that the most important reasons why contractors did not fulfill their contractual requirements in building projects were that contracts were awarded to the contractor offering the lowest price, and the profit margin was low because of intense competition among contractors. In road projects, the most important causes were the poor estimation of the equipment required and a lack of standardized conditions in the construction sector, while in electro-mechanical projects, the most important causes were the inability of the contractor to estimate the cost of the project accurately because of unclear bid documents and a lack of contractor capital.Originality/valueThe results of this study will be useful to stakeholders and Palestinian contractor unions. They can be disseminated to give guidance so that contractors can avoid these problems in future construction projects and enhance their compliance with contractual requirements. Moreover, knowing about these causes may lead to the reduction of conflicts and disputes between contractual parties (owners and contractors), which in turn will be reflected in the work quality and reputation of contractors.

Purpose: This paper aims to develop an efficient model able to reduce catastrophic consequences and the significant number of victims resulting from fires at construction sites. The paper proposes probabilistic modeling aimed to minimize the probability of failure of a construction site. Methodology: The developed model in this paper consists of modeling fire hazards, the vulnerability of the potential targets, and the risk within construction sites. The optimization algorithm called “differential evolution” is used in order to determine the optimal site layout, which is characterized by having the smallest overall probability of failure. A numerical simulation is performed to delineate an appropriate probability density function of the failure of the site. In addition, a geographic information system (GIS) is used to display the spatial variability of fire risk on a construction site. Findings: The paper provides an efficient model to enhance site layout planning and assign locations for supporting temporary facilities at appropriate positions within a construction site. The model is examined through applying it on a simple case study containing numerous facilities. All these facilities are considered vulnerable targets and some of them are potential fire hazards, with different intensity values. Value: Most of the previous research focuses on travel cost distance in developing site layout planning models. This paper fulfills the development of a valuable model able to generate an optimized construction site layout by minimizing the probability of failure of the whole site. It will assist the decision makers and the risk managers in identifying the riskiest zones on a construction site.